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From |
Joseph Coveney <jcoveney@bigplanet.com> |

To |
Statalist <statalist@hsphsun2.harvard.edu> |

Subject |
Re: st: Modelling two binary outcomes that are not mutually exclusive |

Date |
Sun, 28 Nov 2004 01:31:11 +0900 |

Ronán Conroy wrote: I have two binary outcomes, measured in a patient population (anxiety and depression). For various reasons, I suspect that a number of patient characteristics predict depression but not anxiety. If the two diagnoses were mutually exclusive, all would be well. I could use multinomial logistic regression and compare the coefficients. However, there is about a 20% overlap. Is this a Known Problem? I could model the overlap category as a third outcome, and show that the coefficients were similar to those for depression alone and different to those for anxiety alone, but this is slicing the sample a little thin - there are just 8 people with both disorders. (This approach actually works, sort of, given the small numbers, so I'm on the right track from the theory point of view.) Any suggestions out there? -------------------------------------------------------------------------------- Would -biprobit- (along the lines of Mark Schaffer's suggestion), or -xtprobit- lend any help? As an alternative, would formally modeling as a bivariate binomial regression using -gllamm- (two random effects, one for each outcome, ŕ la Van Houwelingen's bivariate approach to meta-analysis) help? Joseph Coveney clear set more off drawnorm y1 x1 x2, mean(0 0 0) /// sd(1 1 1) corr(1 0.7 0.7 \ 0.7 1 0.7 \ 0.7 0.7 1) /// n(200) seed(`=date("2004-11-28", "ymd")') generate byte y0 = uniform() > 0.5 // y0, Anxiety replace y1 = y1 > 0 // y1, Depression compress pwcorr biprobit y0 y1 x1 x2 // It shows that y1 is predicted and not y0 generate int pid = _n reshape long y, i(pid) j(dep) xi: xtprobit y i.dep*x1 i.dep*x2, i(pid) re // The dependent-variable-by-predictor interaction terms // indicate that one is predicted and not the other (given the // necessary assumptions) exit * * For searches and help try: * http://www.stata.com/support/faqs/res/findit.html * http://www.stata.com/support/statalist/faq * http://www.ats.ucla.edu/stat/stata/

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